Case-Based Reasoning (CBR) involves the recording of a block of situations, to be matched by the context, and producing the closest matching case, which in turn produces the consequent of choice. A strength of CBR is that, unlike the situation for expert systems, a knowledge engineer is not required. One of the major unsolved problems in CBR pertains to how to automatically adapt a retrieved case to not only match the current context, but to adapt its consequent to be a proper match as well. There is a clear need for an adaptive case-based reasoning system and method that addresses the above deficiency in the art.